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Visual object tracking in a parking garage using compressed domain analysis

Published: 12 June 2018 Publication History

Abstract

Modern driver assistance systems enable a variety of use cases which rely on accurate localization information of all traffic participants. Due to the unavailability of satellite-based localization, the use of infrastructure cameras is a promising alternative in indoor spaces such as parking garages. This paper presents a parking management system which extends the previous work of the eValet system with a low-complexity tracking functionality on compressed video bitstreams (compressed-domain tracking). The advantages of this approach include the improved robustness to partial occlusions as well as a resource-efficient processing of compressed video bit-streams. We have separated the tasks into different modules which are integrated into a comprehensive architecture. The demonstrator setup includes a 2D visualizer illustrating the operation of the algorithms on a single camera stream and a 3D visualizer displaying the abstract object detections in a global reference frame.

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Cited By

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  • (2020)Pedestrian Re-identification with Adaptive Feature Dimension Reduction for Vehicle-Road Cooperative Perception2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)10.1109/ITSC45102.2020.9294478(1-6)Online publication date: 20-Sep-2020
  • (2019)Compressed-Domain Video Object Tracking Using Markov Random Fields with Graph Cuts OptimizationPattern Recognition10.1007/978-3-030-12939-2_10(127-139)Online publication date: 14-Feb-2019
  • (2018)Efficient Object Tracking in Compressed Video Streams with Graph Cuts2018 IEEE 20th International Workshop on Multimedia Signal Processing (MMSP)10.1109/MMSP.2018.8547120(1-6)Online publication date: Aug-2018

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  1. Visual object tracking in a parking garage using compressed domain analysis

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    Published In

    cover image ACM Conferences
    MMSys '18: Proceedings of the 9th ACM Multimedia Systems Conference
    June 2018
    604 pages
    ISBN:9781450351928
    DOI:10.1145/3204949
    • General Chair:
    • Pablo Cesar,
    • Program Chairs:
    • Michael Zink,
    • Niall Murray
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    New York, NY, United States

    Publication History

    Published: 12 June 2018

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    Author Tags

    1. automatic driving
    2. compressed-domain analysis
    3. driver-assistance systems
    4. indoor localization
    5. infrastructure-based localization
    6. visual object tracking

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    • Demonstration

    Funding Sources

    • German Federal Ministry for Economic Affairs and Energy

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    MMSys '18
    Sponsor:
    MMSys '18: 9th ACM Multimedia Systems Conference
    June 12 - 15, 2018
    Amsterdam, Netherlands

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    Overall Acceptance Rate 176 of 530 submissions, 33%

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    Cited By

    View all
    • (2020)Pedestrian Re-identification with Adaptive Feature Dimension Reduction for Vehicle-Road Cooperative Perception2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)10.1109/ITSC45102.2020.9294478(1-6)Online publication date: 20-Sep-2020
    • (2019)Compressed-Domain Video Object Tracking Using Markov Random Fields with Graph Cuts OptimizationPattern Recognition10.1007/978-3-030-12939-2_10(127-139)Online publication date: 14-Feb-2019
    • (2018)Efficient Object Tracking in Compressed Video Streams with Graph Cuts2018 IEEE 20th International Workshop on Multimedia Signal Processing (MMSP)10.1109/MMSP.2018.8547120(1-6)Online publication date: Aug-2018

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